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BB self-evolving-memory

Orchestrate the OpenClaw memory system so it actually runs reliably in practice. Use when the task involves capturing user preferences, current task state, corrections, decisions, recurring issues, memory cleanup, memory migration, or deciding where information should live across the workspace memory layers, including hot state, daily memory, structured long-term memory, root summary, and enforcement files such as SOUL.md, AGENTS.md, and TOOLS.md. Also use when the user asks to save memory, remember something, adapt old memories to the new system, or make the memory system actually stick and keep working over time.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: HAL-9909 v1.0.0 MIT-0 14 files · 1 script body ≈ 2 000 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Orchestrate the OpenClaw memory system so it actually runs reliably in practice.

As a process B 65/100 · Nearly there — weak spots: result and completion, inputs and preconditions

ProcedureAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
77
Quality 40%
91
Run on models
none yet
Process rating
B
65/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
60
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 2

  • high Dangerous commands cmd-pipe-to-shell references/embedding-setup.md:16
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    curl -fsSL https://ollama.ai/install.sh | sh
Medium and low: 1
  • medium Broad scope meta-agent-memory-dump templates/HEARTBEAT.md
    Agent memory / workspace files bundled with the skill (6) — likely a workspace dump with personal data or tokens
    templates/HEARTBEAT.md, templates/MEMORY.md, templates/memory/MEMORY.md, templates/memory/preferences.md, templates/memory/projects.md

Files scanned: 14. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

✓ No remarks against the Agent Skills spec

Process rating: all ten parameters 65/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 60Failures and branches. 2 branches
  • 70When it triggers. States when to use, but not when not to
  • 85Steps. 77 steps, 2 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2000 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low 12 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 622: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 77 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

External checks

ClawHub: clean
This skill persistently manages OpenClaw memory files as advertised, with some privacy and control considerations but no artifact-backed malicious behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026